KR101667199B1 - Relative quality index estimation apparatus of the web page using keyword search - Google Patents

Abstract

There is provided a computing device for relatively evaluating the quality of a web page to be analyzed based on a search result web page retrieved from a target search engine through keyword search. The relative quality index evaluation apparatus can calculate the quality index by comparing the results generated by analyzing the reference page and the analysis target web page, which are retrieved from the target search engine, with the same analysis algorithm using the target keyword. At this time, the analysis target becomes an element constituting the web page, and the analysis algorithm can be applied a search optimization criterion corresponding to the search engine.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a web page indexing system,

Relates to a quality index evaluation of a web page, and more specifically to a computing device that relatively evaluates the quality of a web page to be analyzed based on a target keyword and a search result web page that is searched through the target search engine.

American economist Rolland Hall presented the AIDMA theory which shows the consumer's purchasing process step by step. AIDMA theory explains that consumers purchase items in the order of Attention, Interest, Desire, Memory, and Action. Attention to attract consumers to the product through advertisements, Interest that the consumer has interest in the product, Desire that the consumer wants the product, Memory is the step of imprinting the product, and finally, the action that the consumer decides and makes the payment. The steps directly related to marketing are the Attention phase and the Memory phase. In the Attention stage, advertisements are made in various ways to expose products to potential consumers. In the memory stage, companies apply diverse marketing methods to instill good memories in their products.

However, as the social network became common due to the recent development of the Internet, AIDAS theory was reorganized and AISAS theory emerged. The AISAS theory includes Attention, Interest, Search, Action, and Share phases, and new search and search steps are added. Unlike the AIDMA theory, when the purchase is completed, the AISAS theory can repeat the SAS step. In other words, consumers search the Internet for products that interest them, and then share their purchasing experiences with others through social networks. Furthermore, the emergence of smartphones and tablets brought about changes in interest and search in AISAS using existing PCs.

This change in consumption patterns has led to changes in marketing, and marketing has become a new mode of behavior - search and share. However, online contents that consumers create to share product purchases vary in their constituent elements and types, and Internet search results are variable due to various factors such as a search word, a search engine, or a search target as well as contents of online contents It is difficult to predict what contents will be shared in the search phase.

Korean Patent Laid-Open Publication No. 10-2013-0043297, published on March 30, 2013.

According to one aspect, there is provided a computing device comprising at least one processor, the computing device comprising: at least one processor configured to: at least temporarily store: a first A first result analyzing the content by an analysis algorithm and a second result analyzing the second content extracted from the web page to be analyzed by the analysis algorithm; And a computing unit for computing a quality index of the web page to be analyzed by comparing the first result and the second result. The at least one reference page may be ranked at a predetermined level or higher in a search result retrieved from the target search engine by the target keyword as a query, and the predetermined level may be a predetermined number of The reference page can be determined. The first content and the second content may include at least one of a title, a body, a hyperlink, an image, a voice, a moving picture, a keyword, a comment, a sympathy, a tag, a map,

According to an embodiment, the analysis algorithm statistically analyzes the first content, calculates a recommendation value corresponding to a search optimization criterion of the search engine based on the analyzed result, and sets the recommendation value as the first result The search optimization criterion may include the number of characters, the number of keywords in the text, the number of images included, the number of videos included, the number of maps included, the number of comments, the number of empathy, the number of tags, the number of tags included in the keywords, , A title beginning with a keyword, or a map interlock number. The search optimization criterion may be determined corresponding to the target search engine, and the target search engine may be one or more. The analysis algorithm may assign a weight according to a search order to the reference page, and reflect the search order to the recommendation value.

According to one embodiment, the data constituting the reference page may be converted into a document object model (DOM), the first content may be extracted hierarchically from the document object model, The first content can be automatically extracted from the reference page by using a bot having a rule corresponding to the content output method of the user.

According to an embodiment of the present invention, the apparatus further includes an output unit for outputting the quality index, wherein the output unit includes a statistical graph that visually indicates the quality index, can do.

According to another aspect, there is provided a computing device comprising at least one processor, said computing device being implemented at least temporarily by said at least one processor: extracting from at least one reference page retrieved from a plurality of target search engines corresponding to a target keyword A first result obtained by analyzing the first content by a plurality of analysis algorithms corresponding to the target search engine used in the search and a second result obtained by analyzing the second content extracted from the analysis target web page by the plurality of analysis algorithms An analyzing unit to generate; And a computing unit for computing a quality index of the web page to be analyzed by comparing the first result classified with the target search engine and the second result. The operation unit may extract an element common to the target search engine from the first result, set a recommendation value, and further compute a universal index of the analysis target web page by comparing the recommendation value and the second result .

1 is a block diagram illustrating a computing device in accordance with one embodiment.
2 is a diagram illustrating an example of a user using a computing device according to an embodiment.
3 is an example of a result screen retrieved from a target search engine in one embodiment.
4 is an illustration of a web page that may be used in one embodiment.
5 is a block diagram illustrating a web page collection device in one embodiment.
6 is a flowchart of a method for calculating a relative quality index of a web page according to an embodiment.
7 is an example of a result screen retrieved from a plurality of target search engines in another embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the rights is not limited or limited by these embodiments. Like reference symbols in the drawings denote like elements.

The terms used in the following description are selected generally universally in the art to which they relate, but there may be other terms depending on the development and / or change in technology, customs, preferences of the technician, and the like. Accordingly, the terminology used in the following description should not be construed as limiting the technical thought, but should be understood in the exemplary language used to describe the embodiments.

Also, in certain cases, there may be a term chosen arbitrarily by the applicant, in which case the meaning of the detailed description in the corresponding description section. Therefore, the term used in the following description should be understood based on the meaning of the term, not the name of a simple term, and the contents throughout the specification.

FIG. 1 illustrates a computing device 100 according to an embodiment. The computing device 100 may include an analysis unit 110 and an operation unit 120. The computing device 100 can be connected to a network through a communication unit (not shown), and the communication unit can access various kinds of online documents, contents, and data on the network by using various communication means such as wired or wireless. The computing device 100 includes at least one processor, and the analysis unit 110 and the computing unit 120 are implemented at least temporarily by at least one processor. For example, the computing device may be a variety of devices, such as a PC, a server, a smart phone, a tablet, and the like.

Prior to describing FIG. 1, referring to FIG. 2, FIG. 2 is a diagram illustrating an example in which a user 200 uses a computing device 100 according to an embodiment of FIG. Illustrative but non-limiting examples are given below. If the user creates an online bulletin (http://blog.com/20154) and wonders about the quality index searched by the target keyword ("Goodbye restaurant"), the target keyword / Target of evaluation is input. The computing device 100 collects / analyzes other web pages that are searched for "Hong-dae restaurant" as a comparison target, and calculates a quality index for a user's online post. Then, the calculated quality index can be provided to the user as a diagnosis result report or an analysis result report expressed in various types of graphs. In other words, when the user inputs a desired keyword and an evaluation target (analysis target web page), the computing device 100 can provide analysis reports on the quality of the target search engine in comparison with other web pages have. Hereinafter, each component of the computing device 100 will be described in detail.

The analysis unit 110 analyzes the first content obtained by analyzing the first content extracted from the at least one reference page retrieved from the target search engine in accordance with the target keyword with the analysis algorithm and the second result extracted from the analysis target web page The second result analyzed by the algorithm can be generated.

When a keyword is searched by a search engine, keywords included in the web pages or related information are fed back to the search results. A web page to be searched is a generic term of web documents on the Internet. It can be any kinds of online documents, contents, and materials that can be accessed through a network. In addition to various texts, images, sounds, and video files There are features that can be embedded. For example, the web page may be a homepage post, a community post, a question post, an answer post, a blog, an SNS page, a PDF document, and the like. In one embodiment, the relative quality index can be evaluated by performing a keyword search on a web page. Accordingly, the analysis unit 110 analyzes the reference page and the analysis target web page, which are the results of performing the search in the target search engine corresponding to the target keyword. Here, both the reference page and the analysis target web page correspond to the web page and can be searched from the target keyword. However, the reference page and the analysis target web page do not have to be the same kind, The index can be evaluated.

In more detail, the analysis unit 110 analyzes content, which is a component constituting a web page. The first content extracted from the reference page and the second content extracted from the analysis target web page are analyzed. The first content and the second content may include at least one of a title, a text, a hyperlink, an image, a sound, a moving picture, a keyword, a comment, an empathy, a tag, a map, This may be included in the first content and the second content by way of example, but is not limited thereto. If a new presentation prototype occurs on-line, a new prototype may naturally be included in the first content or the second content. That is, all the elements constituting the web page can be the first content or the second content as an analysis target.

The analyzer 110 generates a first result analyzing the first content by the analysis algorithm and a second result analyzing the second content by the same analysis algorithm, respectively. When the first content includes a title, the analysis algorithm can determine the number of characters constituting the title, the font, emphasis, whether the keyword is included, whether the keyword starts with, or the like in order to analyze the title in relation to the target keyword .

The search engine is not one, the search object may be different for each search engine, and the way in which the search result is displayed may vary. 3 is an illustration of a result screen 300 that is retrieved from a targeted search engine in accordance with one embodiment. Since the search results may be arranged differently for each search engine, FIG. 3 will be described as an example.

Referring to FIG. 3, when the target keyword is input to the interface 310 provided by the target search engine and the search 320 is performed, the retrieved reference pages 400 are arranged in the result list 330. Since the number of the reference pages 400 may vary according to the target keyword, when there are a large number of search results, the reference page 400 may be provided by linking N pages to the result list 330 as shown in FIG. Also, if the result screen 300 is different according to the target search engine, the number of reference pages that can be confirmed on one screen may also be changed. This can be determined with respect to the readability of the display device, and can be appropriately selected depending on the implementation environment.

4 is an illustration of a web page 400 that may be used in one embodiment. In one embodiment, the web page 400 may be a reference page or an analysis target web page that is searched with a target keyword. Because the types of web pages are so diverse, Fig. 4 is for illustrative purposes only. The web page 400 includes a title 401, a creation date and time 402, an image 403, a body text 404 that may be composed of text, a tag 405 indicating a word selected by the author in association with the content of the body text, And the like. In FIG. 4, it is a matter of course that the constituent elements represented by expressing some constituent elements may be deleted, or other constituent elements may be added. As described above, the first content and the second content constituting the web page may be constituent elements of the web page 400. [

In one embodiment, the at least one reference page may be ranked at a predetermined level or higher in a search result retrieved from the target search engine as a query target keyword. The reference page refers to a comparison object for calculating the quality index of the web page to be analyzed. It is possible to view all the web pages retrieved by the target keyword as a reference page or only a web page satisfying a predetermined level as a reference page. For example, a web page included in the first screen fed back as a search result may be referred to as a reference page, or a web page included in the search result ranking 100th page may be referred to as a reference page. In addition, since the number or arrangement of the reference pages exposed in correspondence with the display device of the target search engine or the result screen may vary, the actual number of reference pages may be different even at the same designated level.

The predetermined level may be determined as a predetermined number of the reference pages in order of ranking. Quot; can be determined in accordance with the order and the number that is ranked as a search result. The practitioner will be able to select and make appropriate choices according to the purposes for which the quality index is calculated and the subjects to be compared.

The search result corresponding to the keyword search may be different according to the search optimization criterion. Search Engine Optimization (SEO) is an index that assigns a ranking to a search result by a search engine. Search optimization criteria may vary depending on the search engine. For example, as the search optimization criterion meets the search criteria, the web page will be arranged in a higher search ranking. When the keyword related to the product is used as a keyword in the search process of the AISAS theory, it is likely that the web pages meeting the search optimization criteria are likely to be exposed to the prospective consumers. On the other hand, The greater the likelihood of sharing with others. Therefore, the search optimization criterion can be determined according to the search engine, and if the quality index of the web page is calculated according to the search optimization criterion in the target search engine, the search optimization criterion can be utilized for the marketing means of the search engine.

The analysis unit 110 of FIG. 1 uses an analysis algorithm to generate a first result and a second result, in one embodiment, the analysis algorithm statistically analyzes the first content and, based on the analyzed result, A recommendation value corresponding to a search optimization criterion (SEO) of a search engine may be calculated and set as a first result.

Search optimization criteria (SEO) is based on the number of characters, the number of keywords in the text, the number of images included, the number of sounds included, the number of videos included, the number of images included, the number of maps included, the number of comments, Keyword inclusion, keyword inclusion, keyword subject inclusion, or map interworking. This is not to be construed as limiting the invention to the exemplary embodiment, and it is to be understood that any element of the search optimization criteria (SEO) may be used as an indicator for evaluating components (e.g., first content or second content in an embodiment) It can be a component. For each search engine, the number and type of components included in the Search Optimization Standard (SEO) may vary, and the weight may be given differently for each component.

On the other hand, the analysis algorithm can assign the weight according to the retrieval rank to the reference page, and reflect the search ranking in the recommendation value. In other words, the popularity of posts will have a greater impact on setting the recommendation value than a regular post. Most popular posts are based on the search optimization criteria of the target search engine.

Referring back to FIG. 1, the computing unit 120 may compute the quality index of the web page to be analyzed by comparing the first result generated by the analyzing unit 110 with the second result. The quality index is a relative index in which a web page is determined in comparison with at least one reference page retrieved from a target search engine corresponding to a target keyword. The quality index is calculated by comparing the first result and the second result relatively. Specifically, the first result is statistically analyzed, and then the second result is compared based on the calculated recommendation value based on the analyzed result, .

The following describes an exemplary quality index calculation method in one embodiment.

a _k denotes each item of the first content, and A _i denotes an average of the sum of each item of the first content value of the reference page. Alternatively, a _k represents each item of the second content, and A _i represents an average of the sum of each item of the second content value.

A certain amount of data ranked at the top of the reference page may be meaningless data, such as an excessive content posting, and therefore should be excluded from analysis. Also, a certain amount of data ranked at the bottom of the reference page can also be regarded as meaningless data because the observed numerical values are converted and ranked in search order. Therefore, after inserting 10% of each rank ranked in the uppermost (max) and lowest (min), the normalized recommended value d _i can be calculated as shown in the following Equation 2.

The equation for calculating the quality index from the second result corresponding to each item of the second content using Equations (1) and (2) can be defined as Equation (3) below.

The variables in Equation (3) are as shown in Equations (1) and (2), and are calculated as percentiles. It corresponds to each item of the second content, and therefore, the percentile score can be known for items such as the date and time of creation and the number of characters.

It is easy to understand the quality of the web page to be analyzed intuitively because the quality index obtained by comparing the target web page with the reference page that is searched by the target keyword is calculated as an absolute value. As the quality index is higher, it means that it is similar to the top ranked web page among the reference pages searched by the target keyword, and other criteria (search optimization criteria) are applied according to the target search engine. Therefore, It is possible not only to predict the ranking of the target web page but also to grasp the shortage through the item of the quality index for the second result.

In one embodiment, the apparatus may further include an output unit for outputting the quality index. The output unit may provide a guide including an analysis content description prepared in advance according to the quality index and a recommendation preparation method. For example, you might include a qualitative description of the content such as "The number of characters is sufficient" based on the percentile score, and in response to the analysis description "The date and time of creation is too long" You can suggest a recommended feldspar method such as. It is an example to provide an analysis report in FIG. 2, and feedback can be given to the operator through various methods that can express such a guide visually.

FIG. 5 is a block diagram illustrating a web page collection apparatus 500 according to an exemplary embodiment of the present invention. Referring to FIG. 5, a web page to be compared and a method for collecting first content from the web page will be described in detail. The web page collection device 500 may receive a target keyword and an evaluation target from a user, and may assign a task to the schedule module 510 to calculate a relative quality index for the evaluation target. The schedule module 510 may store the target keyword, the URL information to be evaluated, and the like in the storage module 550. Then, the evaluation object can be registered in the waiting task queue to sequentially perform the comparison object collection. The waiting task queue is composed of a plurality of virtual work modules (Job1, Job2, ...), and the virtual work module can collect web pages using a plurality of scrapping bots (520). Approximately 100 scrapping bots 520 are assigned to the necessary tasks while calling the standby job queue. At this time, because the retrieved results may not be in the same domain region, the cross domain control module 530 may automatically scrap an upper-ranked reference page of a predetermined level of a specific portal site. Scrapping bots 520 can automatically collect data with sub-modules while automatically scraping reference pages. The sub-module may be a classification module capable of classifying contents such as a title, a text, an image, or the like, or a filtering module capable of automatically removing an advertisement or the like. The data collected by the scraping bots 520 may be subjected to a step of secondarily extracting the first content by the acquisition module 540. The raw data itself is collected, converted from the collected raw text data into a document object model (DOM), and converted into a form capable of hierarchical data collection. And collect data by items such as title, meta tag, number of text, number of emphasis, current rank, and so on. This can be determined according to the elements constituting the raw data. Finally, you can collect hypermedia such as images, videos, links, and so on. The collected data may be stored in the storage module 550 corresponding to the first content item in a processed state, and then the stored data may be updated. In this way, in one embodiment, the reference page can be collected and the first content can be automatically extracted. It will be appreciated that this may be done differently depending on the implementation environment in an exemplary manner.

In one embodiment, the data constituting the reference page is converted into a document object model (DOM), and the first content can be extracted hierarchically from the document object model. The document object model is an object-based document model for interoperability of XML (Extensible Markup Language) documents through a web browser. It is a platform and language-neutral interface, and it is a dynamic of document contents, structure, It is possible to easily extract the first contents constituting the reference page by using the document object model in this embodiment.

The first content can be automatically extracted from the reference page by using a bot having a rule corresponding to the content output method of the target search engine. The first content can be automatically extracted using the bot when the comparison object, that is, the reference page, is large, so that it can be time-efficient.

A process for calculating a quality index of a web page to be analyzed by a computing apparatus according to an exemplary embodiment will be described in more detail with reference to exemplary values.

Table 1 is an example showing the first result generated from the N reference pages (RP). SEO is Search Engine Optimization, unit is the unit for SEO value, RP 1, RP 2, RP 3, ... , RP N means N reference pages.

SEO unit RP 1 RP 2 RP 3 ... RP N One Date and Time Day (current basis) -2 -4 -5 -156 2 Include keyword headers Included / Not included include include include Without 3 Number of characters dog 1279 900 1202 576 4 Number of keywords in the body dog 3 3 4 One 5 Number of images uploaded dog 15 14 12 5 6 Comments dog 42 38 12 3 7 Empathy number dog 24 8 40 0

Table 2 is an example showing the second result generated from the analysis target Web page (User Page). The web page to be analyzed can be an online post written by the user.

SEO unit User Page One Date and Time Day (current basis) 0 2 Include keyword headers Included / Not included Without 3 Number of characters dog 1100 4 Number of keywords in the body dog 4 5 Number of images uploaded dog 10 6 Comments dog 10 7 Empathy number dog 10

The first result of Table 1 and the second result of Table 2 show the result calculated by the same analysis algorithm of the analysis unit 110 in one embodiment. Therefore, it can be seen that the analysis result for the same item is calculated. As shown in Tables 1 and 2, the first result and the second result can be made of a combination of a plurality of values rather than a single value.

Table 3 is a table showing recommendation values (Guideline) calculated from the first result of Table 1. < tb > < TABLE > The recommendation value means the degree to which the target search engine affects the search ranking.

SEO unit Guideline One Date and Time Day (current basis) -7 2 Include keyword headers Included / Not included include 3 Number of characters dog 1698 4 Number of keywords in the body dog 3 5 Number of images uploaded dog 18 6 Comments dog 23 7 Empathy number dog 14

In Table 3, the recommendation value of the creation date and time is -7, which indicates 7 days before the current standard, and corresponds to the search optimization criterion, which means that it can have a high search ranking up to the web page created 7 days before. Also, the recommendation value of the number of characters is 1698, which means that the total number of characters in the web page is not enough to meet the search optimization criterion. It is more meaningful to interpret the search optimization criterion as a combination of items and a recommendation value thereof rather than a separate value of each item. As described above, the search optimization criteria may be different for each search engine.

Table 4 is a table showing the quality indexes for calculating the normalized value and the percentile score of the web page to be analyzed by comparing the recommendation value (Table 3) with the first result (Table 2) of the web page to be analyzed. In one embodiment, the quality index is calculated as a percentile score, and a quantitative analysis result of the web page to be analyzed can be presented to the practitioner.

SEO unit guideline User Page Normalization value score
(point) One Date and Time Day (current basis) -7 0 0.24 40 2 Include keyword headers Included / Not included include Without 0.5 100 3 Number of characters dog 1698 1100 0.77 62 4 Number of keywords in the body dog 3 4 0.88 88 5 Number of images uploaded dog 18 10 0.95 56 6 Comments dog 23 10 0.44 40 7 Empathy number dog 14 10 0.57 50

The creation date and time of Table 4 can be interpreted intuitively as 40 points, which means that the quality is low, and the keyword title is 100 points, the quality is high, and the number of characters is 62 points.

The output unit for outputting the quality index can output the quality index as shown in Table 4, and can further include qualitative analysis result contents according to the score and a recommendation creation guide. Analysis and countermeasures can be given to the operator.

6 is a flowchart of a method of calculating a relative quality index of a web page according to an exemplary embodiment of the present invention, and illustrates a method of calculating a relative quality index in a target search engine in response to a target keyword, . In step S610, the user can input the target keyword and the evaluation target. In step S620, the search may be performed using the target keyword received from the target search engine, and the search result may be collected as a reference page. In this process, the comparison objects can be automatically extracted using the web page collection device as shown in FIG. In step S630, the first content is extracted from the collected reference page. Further, the second content can be extracted from the web page to be evaluated. The first content and the second content correspond to the constituent elements of the web page, and may be various types such as title, text, sound, image, moving image, tag, and the like.

In step S640, the first content and the second content are analyzed. It is possible to generate the first and second results of analyzing each content item by using the same analysis algorithm. For example, the subject may include analysis such as whether the keyword is included. In step S650, the second result of the evaluation object is compared with the first result of the reference page to be compared. At this time, it is possible to perform an arithmetic comparison using statistical methods, and detailed comparisons can be made according to the units of each item. In particular, a method may be used in which a recommended value is calculated using a first result according to a search optimization criterion (SEO) in a target search engine, and the recommended value is compared with a second result. The relative quality index can be calculated by comparing the comparison object with the evaluation object in various ways.

Then, in step S660, a comparison result report including the quality index can be generated. The result of the comparison can be made up of a quality index expressed as a percentile score or a comparative graph that can be visually compared with reference pages and provides useful information to the user.

FIG. 7 is an illustration of a result screen 300 that is retrieved from a plurality of target search engines in accordance with another embodiment. There are one or more search engines, and each search engine is different from the database to be searched, the search algorithm, and the method of placing the search results. Accordingly, another embodiment provides a computing device that calculates a quality index of a web page to be analyzed using a plurality of target search engines.

A computing device comprising at least one processor according to another embodiment includes an analyzer and an arithmetic unit implemented at least temporarily by the at least one processor.

The analysis unit generates a first result obtained by analyzing first content extracted from at least one reference page retrieved from a plurality of target search engines in correspondence with a target keyword with a plurality of analysis algorithms corresponding to a target search engine used for the search do. Since the first result is generated corresponding to the target search engine used for the search, the contents of the first result can be classified according to the type of the target search engine. The analyzer generates a second result analyzing the second content extracted from the web page to be analyzed by the plurality of analysis algorithms. Since the second result is also a result of analyzing with a plurality of analysis algorithms corresponding to a plurality of target search engines, the contents of the second result can be classified according to the type of the target search engine. The first content and the second content may include at least one of a title, a text, a hyperlink, an image, a sound, a moving picture, a keyword, a comment, a sympathy, a tag, a map, On the other hand, the analysis unit (110 in FIG. 1) of the embodiment can be interpreted the same as the first result and the second result are repeatedly performed for a plurality of target search engines. Therefore, the analysis unit 110 of FIG. 1 can be included in the analysis unit of another embodiment, and detailed description thereof will not be repeated.

The operation unit compares the first result classified with the target search engine and the second result to calculate a quality index of the web page to be analyzed. In both the first and second results, the contents can be classified according to the type of the target search engine, and the relative comparison can be made for each item. Also, the operation unit may extract an element common to the target search engine from the first result, set a recommended value, and then compute the universal index of the web page to be analyzed by comparing the recommended value and the second result. Search optimization criteria may be different for each search engine, so that a recommended value can be set by extracting a common element among the search optimization criteria. For example, if all the search optimization criteria of the search engine used in the search are commonly included in the number of characters and the number of images, the recommendation value for these items can be calculated without discriminating the target search engine. A universal index is an index that can be ranked at the top of a plurality of search engines for an online post (web page). For example, if the universal index is high, it means that all the search engines can be ranked in the upper rank. If the universal index is low, it means that only the specific search engine can rank the rank. In another embodiment, by using a plurality of search engines, it is possible to have a effect of expanding a reference page to be compared, and at the same time, calculate whether or not it meets a web page quality evaluation standard commonly sought by a plurality of search engines Feedback.

On the other hand, the at least one reference page may be ranked at a predetermined level or higher in a search result retrieved from the target search engine by the target keyword as a query. The predetermined level is determined by a predetermined number of the reference pages in order of ranking, and may be variable for each target search engine.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device As shown in FIG. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

  While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

100: computing device
110:
120:
200: User
300: Search engine
400: Web page
500: Web page collection device

Claims (17)

CLAIMS What is claimed is: 1. A computing device comprising at least one processor, said computing device being implemented at least temporarily by the at least one processor:
A first result analyzing a first content extracted from at least one reference page retrieved from a target search engine in accordance with a target keyword with an analysis algorithm and a second result analyzing a second content extracted from the analysis target web page with the analysis algorithm 2 < / RTI > And
An operation unit for comparing the first result and the second result to calculate a quality index of the web page to be analyzed;
Lt; / RTI >
Wherein the analyzing unit analyzes the first content including text data and image, sound, and moving picture data classified with the text data, and the arithmetic unit calculates data existing within a predetermined rank range of the first result, ≪ / RTI >
Wherein the at least one reference page includes a plurality of reference pages, wherein the at least one reference page includes a plurality of reference pages, excluding a first amount of data in an order ranked in the highest order in a search result retrieved from the target search engine, Is determined as the reference page except for the second amount of data,
Wherein the analyzing unit generates the first result using a filtering module that automatically removes an advertisement page,
Wherein the operation unit extracts common elements among search optimization criteria of the target search engine and other search engines to set a recommended value and compares the recommended value with the second result to determine whether the analysis target web page is a search engine And calculates a universal index indicating an index that can be ranked in the upper order. delete delete The method according to claim 1,
Wherein the first content and the second content are content-
A title, a text, a hyperlink, an image, a sound, a video, a keyword, a comment, an empathy, a tag, a map, or a creation date and time. delete The method according to claim 1,
The search optimization criterion may include:
The number of keywords in the text, the number of images included, the number of images included, the number of images embedded, the number of embedded images, the number of embedded images, the number of comments, the number of symmetries, the number of tags, A title, a title, or a map interlock number. The method according to claim 1,
Wherein the search optimization criterion is determined corresponding to the target search engine. The method according to claim 1,
Wherein the analysis algorithm assigns a weight according to a search order to the reference page and reflects the search ranking to the recommendation value. The method according to claim 1,
Converting the data constituting the reference page into a document object model (DOM), and extracting the first content hierarchically from the document object model. The method according to claim 1,
Wherein the first content is automatically extracted from the reference page using a bot having a rule corresponding to a content output method of the target search engine. The method according to claim 1,
And an output unit outputting the quality index,
The output unit includes: Providing a statistical graph visually indicating the quality index, or providing a guide including an analysis content description and a recommendation creation method that are prepared in advance according to the quality index. CLAIMS What is claimed is: 1. A computing device comprising at least one processor, said computing device being implemented at least temporarily by the at least one processor:
A first result obtained by analyzing a first content extracted from at least one reference page retrieved from a plurality of target search engines corresponding to a target keyword by a plurality of analysis algorithms corresponding to a target search engine used for the search, An analysis unit for analyzing the second content extracted from the page with the plurality of analysis algorithms to generate a second result; And
A calculation unit for calculating a quality index of the web page to be analyzed by comparing the first result classified with the target search engine and the second result;
Lt; / RTI >
Wherein the analyzing unit analyzes the first content including text data and image, sound, and moving picture data classified with the text data, and the arithmetic unit calculates data existing within a predetermined rank range of the first result, ≪ / RTI >
Wherein the at least one reference page includes a plurality of reference pages, wherein the at least one reference page includes a plurality of reference pages, excluding a first amount of data in an order ranked in the highest order in a search result retrieved from the target search engine, Is determined as the reference page except for the second amount of data,
Wherein the analyzing unit generates the first result using a filtering module that automatically removes an advertisement page,
Wherein the operation unit extracts common elements among search optimization criteria of the target search engine and other search engines to set a recommended value and compares the recommended value with the second result to determine whether the analysis target web page is a search engine And calculates a universal index indicating an index that can be ranked in the upper order. delete delete delete 13. The method of claim 12,
Wherein the first content and the second content are content-
A title, a text, a hyperlink, an image, a sound, a video, a keyword, a comment, an empathy, a tag, a map, or a creation date and time. A program stored on a computer readable medium for causing a computing device to calculate a web page quality index and provide feedback, the program comprising:
A first result analyzing a first content extracted from at least one reference page retrieved from a target search engine in response to a target keyword received by the computing device by an analysis algorithm, and a second result extracted from the analysis target web page, An instruction set for generating a second result analyzed by the algorithm; And
Calculating a quality index of the web page to be analyzed by comparing the first result and the second result;
Lt; / RTI >
Wherein the analysis algorithm analyzes the first content including text data and image, audio and video data classified with the text data, and the instruction set for calculating the quality index is within a predetermined rank range of the first result And comparing the data to the first result with the second result,
Wherein the at least one reference page includes a plurality of reference pages, wherein the at least one reference page includes a plurality of reference pages, excluding a first amount of data in an order ranked in the highest order in a search result retrieved from the target search engine, Is determined as the reference page except for the second amount of data,
Wherein the instruction set generating the first result comprises a set of instructions relating to a filtering module that automatically removes an advertisement page,
Wherein the command set for comparing the first result and the second result extracts a common element among the search optimization criteria of the target search engine and other search engines to set a recommendation value and sets the recommendation value and the second result And calculating a universal index indicating an index by which the analysis target web page can be ranked higher in a plurality of search engines.

Images